Causal Inference and Discovery in Python Unlock the Secrets of Modern Causal Machine Learning with Dowhy, EconML, Pytorch and More
You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python c...
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| Format: | eBook |
| Language: | English |
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Birmingham
Packt Publishing
2023
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| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Table of ContentsCausality
- Hey, We Have Machine Learning, So Why Even Bother?Judea Pearl and the Ladder of CausationRegression, Observations, and InterventionsGraphical ModelsForks, Chains, and ImmoralitiesNodes, Edges, and Statistical (In)dependenceThe Four-Step Process of Causal InferenceCausal Models
- Assumptions and ChallengesCausal Inference and Machine Learning
- from Matching to Meta-LearnersCausal Inference and Machine Learning
- Advanced Estimators, Experiments, Evaluations, and MoreCausal Inference and Machine Learning
- Deep Learning, NLP, and BeyondCan I Have a Causal Graph, Please?Causal Discovery and Machine Learning
- from Assumptions to ApplicationsCausal Discovery and Machine Learning
- Advanced Deep Learning and BeyondEpilogue